The present invention relates to an information processing system, and specifically to a system for solving a problem through utilization of a knowledge information processing technique (i.e., an artificial intelligence technique) in order to simplify a complicated problem. In particular, the present invention relates to an information processing system suitable to make scheduling, such as a train scheduling system involving trainman scheduling, more intelligent.
The present invention is analogous to U.S. patent application Ser. No. 832, 892 in that a personified model manager is used. While the U.S. patent application Ser. No. 832,892 describes a method for cooperation among a plurality of actors (i.e., a plurality of expert programs which are personified programs simulating the intelligence of experts), the present invention relates to a system for flexibly solving complex problems through goal decomposition that can be embodied even by only a single actor or embodied by multiple actors also.
As disclosed in U.S. Pat. No. 4,648,044, it is hitherto known that knowledge is represented as rules, called production rules, and inference is executed through interpreting the production rules. However, this shows nothing but an inference section (block 13 of FIG. 1) of the present invention and, both basis procedures for achieving goals and adjustment procedures for adjusting the unsatisfactory results are represented as rules. In a complicated problem such as train scheduling including trainman scheduling the number of rules becomes enormous and these rules become entangled (interact or interfere) with each other. This causes problems in processing speed and in reliability.